Explaining value and momentum with macroeconomic risks

By LARRY SWEDROE

Value and momentum are two of the most powerful explanatory factors in finance. Research on both has been published for about 30 years. However, it was not until Clifford Asness, Tobias Moskowitz and Lasse Pedersen published their paper Value and Momentum Everywhere, which appeared in the June 2013 issue of The Journal of Finance, that the two were studied in combination.

Among the findings that Asness, Moskowitz and Pedersen produced were:

consistent return premia on value and momentum strategies were found across asset classes such as equities, fixed income, currencies and commodities, as well as across countries;
even though both return premia were positive, they were negatively correlated; and
despite this negative correlation, a simple equal-weighted combination of value and momentum produced a positive return premium.

Victor Haghani and Richard Dewey, authors of A Case Study for Using Value and Momentum at the Asset Class Level, published in the Spring 2016 issue of The Journal of Portfolio Management, also found that combining the value and momentum factors can offer both higher expected returns and lower risk than when they are used independently. The authors explained that the benefit comes primarily from value and momentum’s tendency to operate over different time horizons: “The negative correlation arises from value investing’s reliance on reversion to fair value (i.e., negative autocorrelation), while momentum investing is predicated on divergence from the mean (i.e., positive autocorrelation). Often, momentum acts as a check on value, discouraging an investor from buying before a bottom or selling before a peak.”

Ilan Cooper, Andreea Mitrache and Richard Priestley contribute to the literature with their study A Global Macroeconomic Risk Model for Value, Momentum, and Other Asset Classes, published in the February 2022 issue of the Journal of Financial and Quantitative Analysis. They examined whether there is a common factor structure related to global macroeconomic risk that can explain the value and momentum factors across many countries and asset classes. They created a global macroeconomic risk factor (CRR) using the following macroeconomic risk factors that have been well established in the literature: the term spread, the default spread, growth of industrial production, change in expected inflation, and unexpected inflation. Their data sample covered the following eight markets and asset classes: U.S. stocks, U.K. stocks, continental European stocks, Japanese stocks, country equity index futures (country indices), currencies, government bonds (fixed income) and commodity futures (commodities), for a total of 48 portfolios. Their sample period was April 1983-December 2018. Following is a summary of their main findings:

The value effect and the momentum effect show up in all the asset classes and across all countries and are statistically significant in most cases. Over all asset classes, the combination return premia ranged from 0.19% for currencies to 0.55% for U.K. stocks.
The value premia were higher in equity markets than in non-equity markets — aggregating across equity markets (global equity) yielded an average excess return of 0.31% compared to 0.19% when aggregating across all non-equity classes (global others).
The momentum premia that were statistically significant ranged from 0.79% per month for U.K. stocks to 0.42% per month for U.S. stocks (which was marginally statistically significant). The aggregated premium was 0.50% per month across the equity classes and 0.23% per month across the non-equity classes, both of which were statistically significant. As in the case of the value return premia, the momentum return premia were higher in equity markets than in non-equity markets. Aggregating across all asset classes (global all), the momentum return premium was 0.34% per month, which was statistically significant.
Although value and momentum return premia were negatively correlated (the negative correlations ranged from -0.68 for global equity to -0.23 for fixed income, and the average correlation coefficient was -0.53), the global CRR factors could also explain the positive return premia on combinations of value and momentum found in the data—the exposure to global macroeconomic risk factors summarises both the average returns of equity portfolios sorted on value and momentum as well as non-equity portfolios sorted on value and momentum, namely currencies, fixed income and commodities.
The combination portfolios were not neutral to global macroeconomic risk even if the value and momentum return premia had opposite sign exposures with respect to the global macroeconomic factors because the exposures were of different magnitudes.
The global CRR factors can explain a reasonable fraction of the cross-section of returns on other international portfolios that are sorted on characteristics that have been recently proposed in the literature, such as profitability, investment, betting-against-beta, quality and size.
Their global CRR model performs better than the three-factor (a global market factor, a global value factor and a global momentum factor) and the Fama-French five-factor (market, size, investment, profitability and value) asset pricing models when the test assets are based on value and momentum.

Of importance is that Cooper, Mitrache and Priestley’s findings provide a risk-based explanation for value and momentum in not only equities but also in currencies, bonds and commodities. Their findings led them to conclude: “The results we present offer a clear indication that global macroeconomic risks have a role in describing the returns on value and momentum strategies and combinations of these strategies across countries and asset classes. Furthermore, the differences in the loadings on the global CRR factors provide a means of describing the negative correlation between value and momentum return premia. Coupled with the ability of the global CRR factors to describe additional test assets returns, this points to a common factor structure across asset classes and countries based on global macroeconomic risk.”

Investor takeaways

First, the research demonstrates that using multiple measures of value and combining value and momentum in a strategy has produced superior results compared to using either just the traditional HML value factor or the traditional momentum factor independently. Such findings explain why we increasingly see fund sponsors use multiple value metrics and combine them with momentum strategies in a single fund.

Second, while there have been many research papers providing risk-based explanations for the value premium (with many showing behavioral explanations as well), researchers have been trying to find a risk-based explanation for the momentum premium for decades without success. Cooper, Mitrache and Priestley’s research findings provide us with the economically rational risk-based explanation, a major contribution to the literature.

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